Abstract—Todays, Intelligent and web-based E-Learning is
one of the important area in E-Learning. This paper integrates
an intelligent and web-based E-Learning with expert system
technology in order to model the learning styles using Jackson’s
model. It is intelligent because it can interact with the learners
and offer them some subjects based on Pedagogy view.
Learning process of this system is in the following. First system
determines learner’s individual characteristics and his learning
style based on a questionnaire in Jackson’s learning styles
profiler. Learning styles profiler is a modern measure of
individual differences in learning style. Then learner’s model is
obtained and an Expert system simulator plans a “pre-test” and
then rates him. The concept would be presented if the learner
scores enough. Subsequently, the system evaluates him by a
“post-test”. Finally the learner’s model would be updated by the
modeler based on try-and-error. The proposed system can be
available Every Time and Every Where (ETEW) through the
web. It has all good facilities such as hypertext component,
adaptive sequencing, problem solving support, intelligent
solution analysis and adaptive presentation. It improves the
learning performance and has some important advantages such
as high speed, simplicity of learning and low cost.
Index Terms—Web-based learning, Expert systems,
Intelligent Tutor, Adaptive Learning, E-Learning, Jackson’s
Model
I. INTRODUCTION
rom 1980, the computers have been applied to develop
electronic learning (E-Learning) systems. Many
researches have been done in this field to improve its
efficiency so far. E-learning can be defined as an activity to
support a learning experience by either developing or
applying information and communication technology (ICT)
[1].
The first E-Learning softwares were using some Medias
such as CDs or Web before. They are static, non-intelligent
and inflexible. Because a course had been organized by prior
procedure and taught in the same style for all learners. They
were either computerized versions of textbooks
(characterized as electronic page turners) or drill and
Manuscript received January 07, 2012; revised January 27, 2012.
Hossein Movafegh Ghadirli is a graduate Student in Computer
Engineering and with Young Researchers Club, Islamshahr Branch, Islamic
Azad University, Islamshahr, Iran. (email: hossein.movafegh@iau-
saveh.ac.ir ; [email protected] )
Maryam Rastgarpour is an instructor with the department of Computer
Engineering, Saveh branch, Islamic Azad University, Saveh, Iran.
(E-mail:[email protected];[email protected])
practice monitors that presented a learner with problems and
compared learner’s responses to pre-scored answers.
Learners are different. It leaded to decrease the efficiency of
this style. It means that some learners need to repeat some
lessons meanwhile some lessons must be removed for others.
Later the researchers concluded that learning process must
be dynamic and intelligent based on pedagogy view [2]. But
developing an applicable and trustful system is so hard [3].
This caused to advent new generation of intelligent
educational systems [4].
A human expert tutor can adapt a proper sequence of
lessons and training speed in according to learner’s aptitude
and characteristics. He can apply some educational tools and
adjust the diction based on learner. He sometimes cancels the
class when learner is not in proper situation. But human
expert tutor is infrequent and expensive. This is another
reason to need to new generation of intelligent educational
systems.
Nowadays, “web-based learning” and “intelligent learning”
is one of the most significant topics in education [3], [5]. A
web-based tutor has some benefits like tirelessly, dominance
on concepts, low cost and invariant of time and place. It can
utilizes conversational agents as well [6]. However millions
learners of the world can learn by thousands of expert tutor
through the web in an intelligent and virtual schools. One of
the important classes of intelligent tutors is based on rule-
based expert system. It determines whatever the student
knows, doesn’t know and knows incorrectly, and uses this
information to adjust learning style. This education type
which derives the benefits of Expert Systems is called model
tracing tutor [4].
This paper introduces an intelligent system to enjoy Expert
Systems abilities. So E-Learning would be efficient, adaptive
and just needs a computer and internet connection. Adapting
with web-based contexts is very important, because the
concept, which is developed for one user, isn’t useful for
others [3].
The proposed system determines the learning style by a
test. So it develops a primary model of learner. The learning
process starts then. Gradually, some characteristics of learner
may be varying during learning progress. These
improvements would be saved by system. So learner model
gets more accurate step by step. System can receives
scientific and mental feedback of learner and then change the
learning style during the process.
A Model for an Intelligent and Adaptive Tutor
based on Web by Jackson’s Learning Styles
Profiler and Expert Systems
H. Movafegh Ghadirli and M. Rastgarpour
F
Web-based learning is useful not only for high level
education environments such as universities but also for
training new employees and adapting staffs according to
company changes. Ideally, web-based learning improves the
learning efficiency for students and employees through
features that are not available in face to face learning. It also
allows learners to access the learning materials and interact
with the rest of course ETEW. The aim of proposed system
is to offer the content which the learner can’t be aware of it
easily.
The rest of this paper is organized as follows. Section II
defines an intelligent E-Learning system and presents some
available samples. It also deliberates adaptive E-Learning,
Jackson Model and learning styles. Section III describes the
proposed E-Learning system which is intelligent, adaptive,
customized and web-based. Finally this paper concludes in
Section IV.
II. BACKGROUND
A. Intelligent E-Learning system
The first intelligent E-Learning systems were computer-
aided instruction (CAI) systems which presented the early
1960’s. Furthermore the adaptive intelligent systems are not
novel at all. All of these systems are a kind of “Intelligent
Tutoring Systems (ITS)” or “Adaptive Hypermedia Systems”
[4].
The late 1960s, ITSs have moved out of the lab and into
classrooms and workplaces where some have been shown to
be highly effective [7], [8]. While intelligent tutors are
becoming more common and proving to be increasingly
effective, they are difficult and expensive to build.
E-Learning systems are classified into two classes:
intelligent and non-intelligent. Non-intelligent systems apply
the same style for variant learners. It is the worst
disadvantage of them, because the learners are various in
terms of awareness and mentality. So it intensely needs to
organize course contents intelligently.
Intelligent systems realize the customized and adaptive E-
Learning based on course content, learner type and
education method [4]. This system can recognize the student
type, choose appropriate course content from knowledge
base and present it to learners in proper style. It also
attempts to simulate a human tutor and act expertly and
intelligently. Students using these systems usually solve
problems and related sub-problems within a goal space, and
receive feedback when their behavior diverges from that of
the learner model. Figure 1 shows the process of intelligent
E-Learning system.
Some available intelligent E-Learning systems are
introduced in Table I to handle the pragmatics of three
elements: content, learner model and education methods for
adaptive and customized learning. These systems have been
validated to simplify learning.
B. Adaptive E-Learning
The adaptive E-Learning has an important role in
efficiency of educational environments. These systems can
also be compatibles with heterogeneous population of
learners. They could defeat similar version of non-adaptive
systems, because an efficient, adaptive and dynamic E-
Learning can recognize learning style of learner based on
pedagogy principles. It can adapt the learners with current
status of system. Then it changes its behavior dynamically
and presents the learning concepts according to learner’s
model.
1) Jackson’s Learning Styles Profiler
This section introduces Jackson model [9].There are some
approaches to model learner’s behavior. For example Entistle
approach [10] tries to make connections between psychology
concepts and effective variables on learner’s view to
‘learning’. Despite they have some benefits in education and
psychology of personality; they are rarely applied in adaptive
education systems.
Jackson’s model is based on the most recent researches in
psychology of personality. It also is efficient analyzer. So this
paper just applies it among available models.
Jackson model has been proposed in Queensland
University [9]. He has investigated personality, learning and
evaluation for fifteen years. Learning is based on new
neurological psychology in this model.
This model has some advantages. For example, it can
report a learner individually. It is obtained on basis of the
points which the learner earns in learning style ( section III-
Fig. 1. Intelligent E-Learning System
TABLE I
SOME AVAILABLE INTELLIGENT E-LEARNING SYSTEMS
Name Comments
CAES system [11] Developed by integration of shipping simulation
and intelligent decision system. The task is to
teach shipping to captains in virtual turbulent
sea.
ICATS [12] Coordinates an expert system with multimedia
system in an intelligent learning system.
ANDES [13] Trains Physics without using natural language.
ATLAS [14] Uses natural language to teach Physics. It can
reply to learner’s questions.
ELM-ART [15] Web-based tutoring System for learning
programming in LISP.
APHID-2 [16] A hypermedia generation system with adaption
by defining rules that map learner information.
AUTOTUTOR [17] Be full intelligent and teach “introduction to
computers” in at least 200 universities of the
world.
B).
The aim of this model is to recognize an ideal style based
on Pedagogy principles which can model learner’s behavior
and specifications in adaptive E-Learning system. A key
premise of Jackson’s model is that cognitive strategies
redirect Sensation Seeking to predict functional behaviors.
2) Learning Styles
Learning styles are various approaches or methods of
learning. An adaptive E-Learning system is based on
accurate recognition of behaviors and individual
characteristics. There are some important factors in learning
style such as aptitude, personality and behavior [2]. It’s
worth to be noted the concept of “learning style” has
emerged as a focal point of much psychological research. In
our proposed learner model, we have adopted the Jackson’s
learning styles profiler in order to model learning styles of
learners. Jackson proposes five learning styles which is
summarizes in Table II.
Sensation Seeking (SS): These people are impulsive and
hurried. New situations are exciting for them so that they
can’t wait and would like to experience and explore it
immediately. They believe to “action” and can perform
multiple tasks simultaneously. These people would rather to
explore their environment by themselves and also learn by
test and error.
Goal Oriented Achievers (GOA): They adjust certain
and difficult aims. They try to increase their abilities by skills
and required cognitive resources in order to realize their
aims. They think troubles are instructive challenges.
Furthermore they believe that can realize to whatever they
want.
Emotionally Intelligent Achievers (EIA): Emotional
independence and rational thinking are their noticeable
characteristics. They are patient learners and can have the
best efficiency after perceiving logic of problem. They can
generalize well and often divide a problem to small and
understandable parts to solve them.
Conscientious Achievers (CA): They are responsible and
clever. They can learn well by collecting, analysis and review
some information before action. They prefer to analyze all
aspects of a problem. Thus they can connect discrete data to
each other and avoid a mistake. These people usually have
extensive knowledge in area of interest.
Deep Learning Achievers (DLA): they have deep
perception of concepts. They want to know how can use
previous knowledge in practice. They can learn well when
they know practical value of something. Thus they can test
that theory or idea. In fact, learning is difficult for them,
when they don’t know the target [2].
III. PROPOSED APPROACH
A web-based, adaptive and intelligent tutor is an E-
Learning system based on web which can be used ETEW. It
can determine learner style, learning content and presentation
technique adaptively. It is updated automatically with
learner’s characteristics and behavior. The first E-Learning
system which is web-based and intelligent, has been reported
on 1995 [4], [18]. Learning of all courses is customized well
at home via web in this system. So learners can solve some
examples and proper exercises ETEW. Finally he can take a
course exam which would be virtual or physical. Figure 2
show the elements of intelligent tutor.
A. Learning Environment
Learner can visits website of intelligent virtual school after
authentication. An intelligent Graphical User Interface (GUI)
is an interface between learners and intelligent tutor. This
section of system can affect learning efficiency. It should be
user friendly.
An intelligent virtual class has some properties such as
graphical properties, audio and video to make learning
attractive. Moreover, some tools are available to simplify
learning process. Learners can communicate well with this
inanimate and non-physical system by these tools. Some
facilities are Computer games, frequently asked questions
(FAQ), Video chat and email.
B. Training Method
Knowledge of expert tutor includes of two parts, learning
content and learning technique. Learning content is theoretic
information, technical content and probably experiments
which expert tutor does. Learning technique is some
experiences which he have got during teaching years [19].
An expert tutor teaches educational content in proper
method by film, dynamic view, game and even puzzle. He
gets feedback from learner during training. So learner level
may be changed than start learning. Tutor helps learner by
“the best way” in proposed model.
The expert tutor offers an education method based on
learner’s type. Furthermore each course section has
individual significance which is different from others. Tutor
often determine different scores for variant sections
according to education method. Moreover he rates highest
one to the most important section of course in all education
methods.
The smallest part of any topic which can’t be divided more
is called “concept”. It is usually equal to a lesson in physical
class. Educational concepts would be transferred to
knowledge base in this system. Then the system can
distinguish all concepts and relocate all parts.
Sometimes a lesson is needed to repeat, relocate or even
TABLE II
SUMMARIZATION OF LEARNING STYLES
Learning
Style Specifications
SS Believing experiences create learning.
GOA Self-confident to achieve difficult and certain target.
EIA Rational and goal-oriented.
CA Responsible and insight creator.
DLA Interested in learning highly.
Fig. 2. Intelligent Tutor Elements
remove for a learner. Most of available systems intelligently
guide a learner to a special aim while only a few intelligent
systems allow leaner to select subsections of a concept.
This system uses a three layered structure to implement a
concept: “Pre-test”, “Learning concept” and “Post-test”.
The pre-test includes of some questions planned by an
expert tutor. These questions can determine learner’s
primary knowledge level. It simulations learner model based
on Jackson model [9]. The learning concept depends on
learner level. So the best method to train a learner is
determined. Afterwards learning process starts up.
Subsequently a post-test evaluate the learner by some
questions. Figure 3 shows block diagram of proposed
system.
In proposed system, the teacher can react in two ways: by
sending a message either to the learner model or directly to
the learner via e-mail. Sending a message to the learner
model is very simple and works even if the learner did not
provide an e-mail address.
C. Learning Evaluation
Learning evaluation is the main factor to determine
learning performance in E-Learning systems. The evaluation
has two levels, conceptual and objective. The first one refers
to learner’s understanding of the lesson concept. The last one
denotes to learner’s understanding of the lesson topic.
Learner’s knowledge level is determined by concept level
and objective level.
The tutor can extract proper questions from question base
by an expert system, pre-test and post-test. He notes that a
specific score is given to each question.
Question selection should satisfy some rules. Firstly none
of them should be repetitious even if a learner would be
trained one concept several times. Secondly the question
must be planned for all sections of a concept entirely. Thirdly
expert tutor plans questions in all level.
Sequence, number and level of questions are determined
according to learner level and learning type intelligently.
Sum of scores is calculated and learner level is determined
after answering the questions. Table III presents five
categories of learner’s knowledge level about a concept [20],
[21].
The modeler of system updates the learner’s model during
progress of answering the questions. It can also save last
academic status of learner and all his learning records.
Table IV summarizes the proposed system and some
available ones in terms of different properties like hypertext
component, adaptive sequencing, problem solving support,
intelligent solution analysis and adaptive presentation [22].
It’s clear in this table that available systems don’t have all of
these useful properties while proposed system has been
designed to covers all.
IV. CONCLUSION
This paper proposed a model for an adaptive, intelligent
and web-based tutor which is able to model the learning
styles of learners using Jackson’s learning styles profiler and
expert system technology to improve learning performance.
Previous E-Learning systems offer fixed multimedia web
pages and facilities for user management and communication.
Based on the proposed model, E-Learning software is
implemented on the web which can identify learning styles,
aptitude, characteristics and behaviors of learner in order to
provide appropriate individual learning content.
Jackson model can recognizes learner’s learning style. It
leads to make learner’s model accurately. So the efficiency of
adaptation process increases.
The proposed model acts as an intelligent tutor which can
perform three processes - pre-test, learning concept and
TABLE III
CATEGORIES OF KNOWLEDGE LEVEL
Knowledge Level Score
Excellent 86-100
Very good 71-85
Good 51-70
Average 31-50
Fig. 3. Web-based Education System
TABLE IV
ADAPTATION TECHNOLOGIES IN WEB-BASED SYSTEMS
System
Hyper
text
Com
ponen
t
Adap
tive
Seq
uen
cing
Pro
ble
m S
olv
ing
Support
Inte
llig
ent
solu
tion
Anal
ysi
s
Adap
tive
Pre
senta
tion
AST Y Y Some
InterBook Y Y Some
PAT-InterBook Y Y Server Y Some
DCG Y Y
PAT Y
WITS N Y
C-Book Y Y
Manic Y Some
Proposed System Y Some Server Y Y
post-test – based on learner’s characteristic. This system uses
expert simulator and its knowledge base as well.
It is also web-based which leads to be low-cost and
available everywhere and every time. Consequently
thousands of students can learn simultaneous and integrated
efficiently.
The proposed system cover all important properties such
as hypertext component, adaptive sequencing, problem
solving support, intelligent solution analysis and adaptive
presentation while available systems have only some of them.
It also doesn’t have any drawback of previous system and
human expert tutor. It can significantly improve the learning
result. In other words, it helps learners to study in “the best
way”.
V. ACKNOWLEDGEMENT
The first author would thank Dr. F. Taghiyareh so much
for her useful guidance during his studying.
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